<i>Nô</i> de Robert Lepage, ou <i>Hiroshima mon amour</i> revu par Feydeau
Bibliographic record
Abstract
Parmi la postérité protéiforme du film-culte d’Alain Resnais, Hiroshima mon amour, il y a Nô (1998) du cinéaste et dramaturge québécois Robert Lepage. Nô constitue un étonnant hommage au chef-d’œuvre de Resnais qu’il croise, de façon tout à fait inédite, avec la comédie-bouffe de Feydeau. Jusqu’à présent, la critique s’est contentée de mentionner au passage la référence intertextuelle sans pour autant montrer à quel point, et a fortiori comment et pourquoi, Nô s’imprègne de l’œuvre de Resnais. Pour peu qu’on s’y attarde, on s’aperçoit que Nô est porté par un étourdissant jeu d’échos, de rappels, et de renvois à Hiroshima mon amour qu’il réfléchit à la manière d’un miroir déformant. Lepage n’y repère pas simplement un cadre exotique pour camper son histoire, il y puise au surplus tout un dispositif narratif qui lui permet de prendre en écharpe la question épineuse de l’Histoire québécoise, des événements d’octobre 1970, et de la mémoire collective.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".